Assessment of Surface Water Quality Using the Water Quality Index (IWQ), Multivariate Statistical Analysis (MSA) and Geographic Information System (GIS) in Oued Laou Mediterranean Watershed, Morocco

Abstract

Surface water is used for a variety of purposes, including agriculture, drinking water, and other services. Therefore, its quality is crucial for irrigation, human welfare, and health. Thus, the main objective is to improve surface water quality assessment and geochemical analysis to evaluate anthropogenic activities’ impact on surface water quality in the Oued Laou watershed, Northern Morocco. Thirteen surface water samples were characterized for 26 physicochemical and biological parameters. In this aspect, emerging techniques such as multivariate statistical approaches (MSA), water quality indices (WQI), irrigation water quality (IWQI), and Geographic Information System (GIS) were employed to identify the sources of surface water pollution, their suitability for consumption, and the distribution of surface water quality. The results showed that the major ion concentrations were reported in the following order: Ca2+, Na+, Mg2+, and K+; and HCO3− > CO32− > Cl− > SO42− > NO3− > F− > PO43− > NO2−. It was also demonstrated that almost all parameters had concentrations lower than World Health Organization (WHO) limits, except for bicarbonate ions (HCO3−) and the biochemical oxygen demand for five days (BOD5), which exceeded the WHO limits at 120 mg/L and 3 mg/L, respectively. Furthermore, the types of Ca2+-HCO3− (Calcium-Bicarbonate) and Ca2+-Mg2+-HCO3− (Calcium-Magnesium-Bicarbonate) predominated in surface water. The Principal Component Analysis (PCA) indicates that the Oued Laou river was exposed to two forms of contamination, the first being attributed to anthropogenic activities such as agriculture, while the second reflects the water-sediment interaction. The Hierarchical Cluster Analysis (HCA), reflecting the mineralization in the study area, has classified the samples into four clusters. The Inverse Distance Weighting (IDW) of the WQI indicates that 7.69% and 38.46% of the surface water represent, respectively, excellent and good quality for drinking. At the same time, the IWQI revealed that 92.30% of the water surface is good for irrigation. As a result, the combination of WQIs, PCA, IWQI, and GIS techniques is effective in providing clear information for assessing the suitability of surface water for drinking and its controlling factors and can also support decision-making in susceptible locations such as the Oued Laou river in northern Morocco.

Assessment Water Quality Indices of Surface Water for Drinking and Irrigation Applications – A Comparison Review

“…Along the river, the readings of BOD5, Na, Cl, Mg, SO 4 , Ca, TH, and NO 3 were higher in the dry season than they were in the wet season, while other readings levels of HCO 3 , EC, TDS, and K were higher in the wet season than they were in the dry season. The results found that the readings of WQI for sites (1-7) classified the WQ for drinking uses as poor, and classified the WQ at sites (8)(9)(10)(11) as good. During the wet and dry seasons in 2016, the Inverse Distance Weighted (IDW) technique, as a tool in the GIS, has used to create the distributing maps of WQI for the total length of the river.…”

Predicting the Production and Depletion of Rare Earth Elements and Their Influence on Energy Sector Sustainability through the Utilization of Multilevel Linear Prediction Mixed-Effects Models with R Software

“…The Mountain Pass deposit in California, discovered in 1949, made Australia and the United States key players. The U.S. dominated production from 1965 to 1995 [45,46]. However, China began to strengthen its industrial power and enter global trade in the late 1970s.…”

Reuse of Treated Wastewater for Crop Irrigation: Water Suitability, Fertilization Potential, and Impact on Selected Soil Physicochemical Properties

“…These indicators provide vital information on the potential risk of sodium and magnesium hazards posed by irrigation water to soil and crops. Below are the equations of the indicators, which were adopted from [34]:…”